Fruit Fly Learning: Operant and classical conditioning

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Presentation transcript:

Fruit Fly Learning: Operant and classical conditioning Björn Brembs, Berlin Fruit Fly Learning: Operant and classical conditioning

Classical conditioning

Operant conditioning Skinner-Box

Operant conditioning Model Critical research must address both stages!

Stage 1: The Actor

The Drosophila Flight Simulator Stage 1: 1/11 The Drosophila Flight Simulator

Stage 1: 2/11 Fly Turning Behavior

Fly Turning Behavior Stage 1: 3/11 Open-loop Model (Robot-Hypothesis) Alternative Hypothesis: Question: Is spontaneous behavior under neural control?

State Space Reconstruction Stage 1: 4/11 State Space Reconstruction Coordinate Embeddings Time series: 80, 60, 40,…… Embedding Dimension: 3 Three data points determine the coordinates of a 3D vector:

Is Turning Behavior Random? Stage 1: 5/11 Is Turning Behavior Random? Analyzing inter-spike-intervals Geometric Random Inner Products: GRIP If Drosophila turning behavior is not random, how is it distributed? Lévy distributed! All calculations: Alexander Maye, UKE Hamburg

Order in Turning Behavior Stage 1: 6/11 Order in Turning Behavior Analyzing inter-spike-intervals Correlation dimension: What is the probability to get the original CD with shuffled data? All calculations: Alexander Maye, UKE Hamburg

Nonlinear Forecasting: S-Maps Stage 1: 7/11 Analyzing inter-spike-intervals Use one part of the series to predict another one Plot the correlation between the two parts Use a weighting parameter to describe the increasing nonlinearity of the models used for the prediction If the correlation increases with the weighting factor, the output is nonlinear All calculations: Alexander Maye, UKE Hamburg

Nonlinear Forecasting: S-Maps Stage 1: 8/11 Analyzing raw yaw torque data series Logistic map: Couplings: All calculations: Alexander Maye, UKE Hamburg

Stage 1: 9/11 Logistic Map

Stage 1: 10/11 Logistic Map

Stage 2: The Critic

Switch Mode Learning Stage 2: 1/2 Two predictors precede the heat (US): color (CS) and behavior Important: each predictor can also be learned separately

Hierarchical Interactions Stage 2: 2/2 Hierarchical Interactions Analyzing sw- and yt-learning How do learning mutants perform in these paradigms? Exchanged contingencies sw-training; yt-test Yoked colors

Take Home Message Operant conditioning consists of two stages. Stage 1 actively initiates a variable range of behaviors. Stage 2 compares outgoing behaviors with incoming sensory data (output/input transformations). Operant conditioning differs from classical conditioning on the behavioral, neural and molecular level. Operant and classical conditioning interact hierarchically in “composite conditioning” to accomplish maximum learning efficiency in natural situations.